The present embodiments relate to adapting activation parameters that are used to generate a pulse sequence when activating a magnetic resonance system.
In the case of known nuclear spin resonance devices, rapidly switched gradient fields of high amplitude are superimposed on a basic magnetic field. As a result of the switching of gradient pulses, the patients may be stimulated by magneto-stimulation in the context of MR examinations. Both humans and animals are considered to be patients in the following. The stimulations are caused by the effect of an electric field on the patient. The electric field in this case is induced by the magnetic flux ϕ=∫BdA, which is generated by each of the three gradient coils as per the Maxwell equations, where B is the magnetic flux density, and A is the area through which the magnetic flux flows. For a specific nuclear spin resonance device, the magnitude of the electric field induced by the switching of a gradient coil is directly proportional to the time-relative change in the magnitude of the magnetic flux Φ and, in the case of a constant flow-through area, also proportional to
      d    ⁢                B              dt(e.g., the time-relative derivation of the magnitude of the magnetic field produced by the gradient coil). Due to the proportionality of electric field and
      d    ⁢                  ⁢    B    dt(the time-relative change in the magnetic flux density B), it is sufficient to examine the time-relative variation of the magnetic flux density B. As a result of the proportionality of magnetic flux density B and the gradient field G for a given gradient coil, an examination of the time-relative change
  d  dtof the location-dependent gradient field G (generally specified in mT/m) is equivalent to the aforementioned examination of the time-relative change
  d  dtof the location-dependent magnetic flux density B (mT). The time-relative variation of the gradient signals is therefore examined in the following. A stimulation occurs when a characteristic threshold value of the electric field is exceeded. For a fixed gradient model, the corresponding threshold value of
            d      ⁢                          ⁢      B                                  ⁢      dt        ⁢          ⁢  or  ⁢          ⁢      dG    dt  depends on the anatomy and the physiology of the patient, the orientation of the patient in the nuclear spin resonance device, and the geometric and physical properties of the three gradient coils.
      d    ⁢                  ⁢    B    dtis given by the amplitude of the gradient pulses and the switching times (rise time). However, in practice, the gradient model is not constant in terms of either the amplitudes or the timing but, in addition to the choice of the measurement sequence to be used, depends, for example, on the chosen measurement parameters (e.g., layer thickness, number of layers, field of view (FOV), matrix sizes, repetition time (TR), echo time (TE), etc.). In this case, in addition to the above cited parameters, the threshold value for the stimulation also depends, for example, on the time-relative structure of the individual gradient pulses, the total number thereof, their repeat rate, and the superimposition of all three gradient coils Gx, Gy and Gz.
In the case of whole-body gradient coils, the stimulation is influenced not only by the Bz component of the magnetic flux, which runs in a longitudinal direction, but also by transverse components Bx and By. The By component is more critical with regard to stimulations since the field lines penetrate the body from the front. Consequently, in the case of a supine or prone position of the patient, the stimulation limit value is to be smallest for the y-axis. In terms of physiology, a stimulation that is performed deliberately using an external electric field may be described very simply in two steps. In this case, the electric field may either act directly from the outside, or be induced by a changing magnetic field.
In a first step, the electric field generates an electric potential at the cell wall of the stimulated nerve cell. The cell wall of the nerve cell may almost be imagined as a capacitance that is charged by the electric field. When the electric potential exceeds a characteristic threshold value, an action potential is triggered in the nerve cell and diffuses over the whole nerve cell. In a second step, at the junction of two nerve cells (e.g., the synapses), an action potential on the pre-synaptic side results in the spilling out of chemical messenger substances (e.g., neurotransmitters). These substances are absorbed on the post-synaptic side (e.g., in the next nerve cell) and trigger a further action potential there. The stimulus diffuses. In this case, the concentration of the messenger substances in the synapse is a measure of the number of action potentials triggered on the post-synaptic side. For example, the concentration of the messenger substances in the synapse only decreases slowly. The characteristic time constant lies in the region of a few milliseconds.
In order to monitor and check the stimulation produced by the magnetic fields of the gradient coils, use is made of look-ahead systems (also referred to as a stimulation checking unit in the following) and realtime monitoring systems (also referred to as a stimulation monitoring unit or realtime monitoring unit in the following). The stimulation checking units may be implemented as a software module and configured such that, when generating pulse sequences, the parameters of the pulse sequences are so adjusted that the stimulation caused by the pulse sequences does not exceed a limit value. In this case, the stimulation checking units also calculate in advance the expected stimulation of a pulse sequence that is generated by a pulse sequence generating unit. If the anticipated stimulation caused by the pulse sequence is below a limit value, the stimulation checking unit outputs a proposal to the pulse sequence generating unit, indicating the activation parameters to be selected for the pulse sequence in order to avoid exceeding the limit value but obtain an optimal imaging result. If the anticipated resulting stimulation caused by the pulse sequence exceeds a limit value, the stimulation checking unit instructs the pulse generating unit to generate a new pulse sequence using different activation parameters. The realtime monitoring systems or stimulation monitoring units may be configured as fixed hardware systems or as digital signal processors with a Harvard architecture, for example, since the process performed by the realtime monitoring systems is very time-critical. A system that is implemented purely as software may be inferior to the hardware systems or digital signal processors in terms of computing speed. The realtime monitoring systems monitor the applicable gradient signals at the gradient coils during the operation of the magnetic resonance system and determine, from the measured physical variables (e.g., the coil voltage and/or the coil current), the stimulation that is generated in each case by the magnetic fields of the gradient coils. If the stimulation exceeds a predefined limit value, the imaging process or sampling process of the magnetic resonance system is terminated immediately in order to prevent excessive exposure of the patient.
The calculation of the stimulation by the stimulation checking units is conventionally only performed for those time segments, of the pulse sequence to be generated, in which the strongest stimulations are expected to occur. The identification of these regions is conventionally performed in advance using the previously known properties of the series of gradient pulses. Depending on the sequence, the identification of these regions may, however, be very difficult and uncertain. In practice, the gradient model is not constant with respect to either the amplitudes or the timing, but, in addition to the choice of the measurement sequence to be used, depends, for example, on the chosen measurement parameters (e.g., layer thickness, number of layers, field of view (FOV), matrix sizes, repetition time (TR), echo time (TE), etc.). The pulse segment having the phase coding step with the strongest gradients may be determined when using, for example, a, SPC sequence, yet the greatest stimulation need not occur in this segment since the stimulation at a specific time point is also dependent on the values of the gradient pulses before and after the cited time point. For example, if the method of flexible reordering is used for an SPC sequence (e.g., the sampling points in the k-space are ideally completed in the automatic mode), or even compressed sensing, the identification of this region is not reliable and depends on many protocol parameters such as, for example, the matrix size, the resolution or the acceleration factor. In addition to the SPC sequence, the cited problems also arise in the case of other sequences (e.g., 3D sequences such as Vibe or TFL). If the pulse segment with a stimulation to be calculated in advance is now enlarged or even extended to include the whole region of the pulse sequence in order to obtain a more reliable result, this would result in very long computing times when using the conventional method as outlined above to calculate the proposal for the activation parameters for a pulse sequence that is to be generated. The resulting time excess is difficult for the operator to accept and is also prevented by the system, since a time limit of 30 s may be set for the individual pulse sequence in order that the process remains tolerable for the operator. However, this provides that the activation parameters used in such a case will with a certain degree of probability generate either a pulse sequence that results in termination by the realtime monitoring system due to unacceptably high stimulation values, or a pulse sequence that would not exceed the stimulation limit value of the patient, which is always defined individually. However, in such a case, the quality of the recorded image may not be optimal, since a pulse sequence that is only just compatible would not be chosen, and there would be a correspondingly significant distance from the maximal compatible stimulation values. Therefore, when using the conventional methods for adapting the activation parameters of a pulse sequence, the problem occurs either that it is not possible to reliably predict whether the stimulation produced in the body of the patient by the pulse sequence will not exceed the predefined limit value, or that the total time of the adaptation process is too long and therefore a less than optimal image result is accepted. In order to overcome or at least slightly lessen the cited problems, provision was previously made, when defining the pulse sequence segments where stimulation is to be calculated, for selecting time intervals or pulse sequence segments that are as long as possible but are still just short enough to remain below the cited time limit for a pulse sequence of 30 s. When determining whether the stimulation produced by the pulse sequence to be generated was still within the predefined stimulation limit value, a tolerance factor was taken into consideration due to the uncertainty that also remained in this case. As before, when using this approach, the selection of pulse sequence segments where stimulation values are calculated is again effected heuristically or according to a criterion that is adversely affected by some uncertainty that the correct region of the pulse sequence is likely to be chosen. As a result of the tolerance factor, the calculation often results in stimulation values that are too high in comparison with the real stimulation values, thereby unnecessarily reducing the output and hence the effectiveness of the pulse sequence that is used. As a result, even when using this optimized approach, negative effects on the measurement time or the image quality may not be prevented. There is even the risk that the image recording may be terminated in the event that, contrary to expectations, the cited tolerance factor was set too low, or incorrect pulse sequence segments were selected for the stimulation value calculation, consequently resulting in sequence terminations at runtime by the stimulation monitoring unit or the realtime monitoring unit as part of the realtime monitoring or online monitoring.